Der Barry, ı am trying to use your way but I couldn't understand how I create sub matrices by using MatCreateSubMatrices() since as input, the function needs const IS instead of IS and I couldn't understand how to get a const IS. I tried to use ISCreateStride since this IS should be 0:71 because as you mentioned, the sub matrix should consist of the entire matrix. However, since ISCreateStride produces IS, not const IS, I couldn't use it in MatCreateSubMatrices().
Thanks Eda Barry Smith <bsm...@petsc.dev>, 10 Haz 2020 Çar, 19:59 tarihinde şunu yazdı: > > > You can use MatCreateSubMatrices() with each process getting a single > sequential dense sub matrix that consists of the entire matrix. > > Use VecDuplicateVecs() to create an array of 72 vectors (create a single > seq vector of size 4 as the input to this routine) > > Then use MatDenseGetArrayRead() to access the upper left corner of the new > sequential dense matrix > > Loop over the vectors calling VecGetArray() > Then loop over the row of the dense array filling up the vector > > Because dense matrices are stored by column, you have to do this looping to > fill up the vectors, they can't share the space with the matrix. > > Barry > > > > On Jun 10, 2020, at 11:36 AM, Matthew Knepley <knep...@gmail.com> wrote: > > On Wed, Jun 10, 2020 at 12:26 PM Eda Oktay <eda.ok...@metu.edu.tr> wrote: >> >> Matthew Knepley <knep...@gmail.com>, 10 Haz 2020 Çar, 19:13 tarihinde >> şunu yazdı: >> > >> > On Wed, Jun 10, 2020 at 12:07 PM Eda Oktay <eda.ok...@metu.edu.tr> wrote: >> >> >> >> Der Matt, >> >> >> >> When I looked at the results, I found that there are some problems I >> >> couldn't understand. >> >> >> >> First of all, I am working on a 72*4 matrix and as I said before, I >> >> want to have 72 different vectors having size 4 each, whose elements >> >> consist of the elements in the same row. And of course, all vectors >> >> should be in all processors (currently I am using 4 processors). >> >> >> >> When I use your scatter code, the output vector is divided into 4 >> >> parts for 4 processors and each vector consists of 18 row vectors >> >> whose elements are arranged in a way that if I want to find zeroth row >> >> vector, its elements are located in 0th,18th,36th,54th elements. >> > >> > >> > Was the global size of the vector you wrapped around the dense matrix 72*4? >> >> Yes it is. I set up its global size to 72*4. >> >> > >> > If you use CreateToAll(), it will make a vector on each process which has >> > the global size of the original vector. >> >> Although I set 72*4, the size of the vectors in each process is 72. > > > You can understand how it is hard to accept, as this code is tested every > night. Can you VecView() the input vector > to CreateToAll and the output vector, and send that output? > > Thanks, > > Matt > >> >> Thanks, >> >> Eda >> >> > >> > Thanks, >> > >> > Matt >> > >> >> >> >> So, isn't scatter's goal is to scatter all values to all processors? >> >> >> >> Furthermore, I am trying to use my vectors in that way but isn't there >> >> any possible way that I can reach my goal entirely? >> >> >> >> Thanks so much for your help, >> >> >> >> Eda >> >> >> >> Matthew Knepley <knep...@gmail.com>, 10 Haz 2020 Çar, 18:11 tarihinde >> >> şunu yazdı: >> >> > >> >> > On Wed, Jun 10, 2020 at 10:09 AM Eda Oktay <eda.ok...@metu.edu.tr> >> >> > wrote: >> >> >> >> >> >> Dear Matt, >> >> >> >> >> >> I have one last question I believe. Up to creating a dense matrix I >> >> >> did what you've suggested. Thank you so much for that. >> >> >> >> >> >> I created a new dense matrix. Now, how should I wrap each vector in a >> >> >> MatDense again? I mean, what is wrapping vectors in a matrix? To put >> >> >> each of them again as rows? >> >> > >> >> > >> >> > I thought you need a dense matrix for something, since you started with >> >> > one. If you >> >> > do not, just do VecGetArray() on the vector from CreateToAll and use >> >> > the values. >> >> > >> >> > Thanks, >> >> > >> >> > Matt >> >> > >> >> >> >> >> >> Thanks! >> >> >> >> >> >> Eda >> >> >> >> >> >> Matthew Knepley <knep...@gmail.com>, 10 Haz 2020 Çar, 16:16 tarihinde >> >> >> şunu yazdı: >> >> >> > >> >> >> > On Wed, Jun 10, 2020 at 9:08 AM Eda Oktay <eda.ok...@metu.edu.tr> >> >> >> > wrote: >> >> >> >> >> >> >> >> Dear Matt, >> >> >> >> >> >> >> >> Matthew Knepley <knep...@gmail.com>, 10 Haz 2020 Çar, 16:03 >> >> >> >> tarihinde >> >> >> >> şunu yazdı: >> >> >> >> > >> >> >> >> > On Wed, Jun 10, 2020 at 8:56 AM Eda Oktay <eda.ok...@metu.edu.tr> >> >> >> >> > wrote: >> >> >> >> >> >> >> >> >> >> Hi all, >> >> >> >> >> >> >> >> >> >> I am trying to get all the rows of a parallel matrix as >> >> >> >> >> individual >> >> >> >> >> vectors. For instance, if I have 72*4 matrix, I want to get 72 >> >> >> >> >> different vectors having size 4. >> >> >> >> >> >> >> >> >> >> As far as I understood, MatGetRow is only for local rows, so >> >> >> >> >> MatGetOwnershipRange is used, however, when I tried this one, I >> >> >> >> >> couldn't get the whole and desired row vectors. >> >> >> >> >> >> >> >> >> >> In MatGetRow explanation, it is written that I should use >> >> >> >> >> MatCreateSubMatrices first, then use MatGetRow. But I couldn't >> >> >> >> >> understand to which extent I should create submatrices. I just >> >> >> >> >> need to >> >> >> >> >> have all 72 rows as 72 different vectors each having 4 elements. >> >> >> >> > >> >> >> >> > >> >> >> >> > 1) For sparse matrices, the storage is always divided by row, so >> >> >> >> > that values can only be retrieved for local rows with MatGetRow() >> >> >> >> > >> >> >> >> > 2) Is this matrix sparse? It sounds like it is dense. >> >> >> >> >> >> >> >> Matrix is dense. >> >> >> >> >> >> >> >> > >> >> >> >> > 3) Are you asking to get all matrix values on all processes? If >> >> >> >> > so, I think the easiest thing to do is first wrap a Vec around the >> >> >> >> > values, then use VecScatterToAll(), then wrap each one in a >> >> >> >> > MatDense again. >> >> >> >> >> >> >> >> Yes, I want all row vectors on all processes. In a dense matrix, >> >> >> >> should I still wrap a Vec around the values? I know I should use >> >> >> >> scatter but I couldn't even wrap a Vec around them. >> >> >> > >> >> >> > >> >> >> > I would do >> >> >> > >> >> >> > MatGetSize(&N); >> >> >> > MatGetLocalSize(&m); >> >> >> > >> >> >> > https://www.mcs.anl.gov/petsc/petsc-current/docs/manualpages/Mat/MatDenseGetArray.html >> >> >> > <create vector of local size m*N> >> >> >> > >> >> >> > https://www.mcs.anl.gov/petsc/petsc-current/docs/manualpages/Vec/VecPlaceArray.html >> >> >> > >> >> >> > https://www.mcs.anl.gov/petsc/petsc-current/docs/manualpages/Vec/VecScatterCreateToAll.html >> >> >> > <do scatter> >> >> >> > >> >> >> > https://www.mcs.anl.gov/petsc/petsc-current/docs/manualpages/Vec/VecResetArray.html#VecResetArray >> >> >> > >> >> >> > https://www.mcs.anl.gov/petsc/petsc-current/docs/manualpages/Mat/MatCreateDense.html >> >> >> > <use it> >> >> >> > <destroy matrix> >> >> >> > <destroy vector from CreateToAll> >> >> >> > >> >> >> > Thanks, >> >> >> > >> >> >> > Matt >> >> >> > >> >> >> >> >> >> >> >> Thanks so much! >> >> >> >> >> >> >> >> Eda >> >> >> >> >> >> >> >> > >> >> >> >> > Thanks, >> >> >> >> > >> >> >> >> > Matt >> >> >> >> > >> >> >> >> >> >> >> >> >> >> Thanks! >> >> >> >> >> >> >> >> >> >> Eda >> >> >> >> > >> >> >> >> > >> >> >> >> > >> >> >> >> > -- >> >> >> >> > What most experimenters take for granted before they begin their >> >> >> >> > experiments is infinitely more interesting than any results to >> >> >> >> > which their experiments lead. >> >> >> >> > -- Norbert Wiener >> >> >> >> > >> >> >> >> > https://www.cse.buffalo.edu/~knepley/ >> >> >> > >> >> >> > >> >> >> > >> >> >> > -- >> >> >> > What most experimenters take for granted before they begin their >> >> >> > experiments is infinitely more interesting than any results to which >> >> >> > their experiments lead. >> >> >> > -- Norbert Wiener >> >> >> > >> >> >> > https://www.cse.buffalo.edu/~knepley/ >> >> > >> >> > >> >> > >> >> > -- >> >> > What most experimenters take for granted before they begin their >> >> > experiments is infinitely more interesting than any results to which >> >> > their experiments lead. >> >> > -- Norbert Wiener >> >> > >> >> > https://www.cse.buffalo.edu/~knepley/ >> > >> > >> > >> > -- >> > What most experimenters take for granted before they begin their >> > experiments is infinitely more interesting than any results to which their >> > experiments lead. >> > -- Norbert Wiener >> > >> > https://www.cse.buffalo.edu/~knepley/ > > > > -- > What most experimenters take for granted before they begin their experiments > is infinitely more interesting than any results to which their experiments > lead. > -- Norbert Wiener > > https://www.cse.buffalo.edu/~knepley/ > >